Building AI-Ready Infrastructure In A Power-Constrained World Ft. Anil Nama, CIO At CtrlS Datacenters

In this episode of TechDogs Discover Dialogues, host Vikramsinh Ghatge sits down with Anil Nama, CIO at CtrlS Datacenters, to explore what it genuinely takes to build infrastructure that supports AI workloads at scale. The conversation moves well beyond technology procurement and into the structural forces shaping where and how data centres get built: power sourcing, cooling innovation, data sovereignty, and the evolving split between public cloud, private infrastructure, and hybrid models.

The demand for AI infrastructure is accelerating faster than the ecosystem can respond. GPU manufacturing capacity for the next 18 months is already reserved. Power consumption per rack is growing sharply. Water usage is under regulatory scrutiny. And data residency mandates are creating new constraints on where critical workloads can reside. Against this backdrop, the question is no longer whether to invest in infrastructure but how to do it without creating downstream risks in energy, sustainability, and compliance.
 

India's Structural Advantage In AI Infrastructure

Anil makes a compelling case that India is structurally positioned to be a global hub for AI infrastructure investment, not simply because of cost, but because of how the country is solving upstream constraints that are far harder to address in developed markets. With renewable energy additions exceeding national data centre demand and solar tariffs in India running at roughly one-third of equivalent contracts in the US or Europe, the economics of building and operating at scale are materially different here.

The grey water cooling model CtrlS is developing is one of the episode's most striking examples. Rather than drawing from potable sources, data centres can be sited to use treated grey water from municipal sewage treatment plants, a model that is commercially viable, supports civic infrastructure, and in Mumbai alone could save an estimated 100 million litres of potable water per day.
 

The Three Sustainability Levers

 

• Power: Sourcing renewable energy at grid scale, investing in PUE reduction from 1.78 down to 1.2 and below through immersion cooling and dielectric fluid technology.

• Water: Rerouting grey water from STP plants to eliminate dependence on potable sources, turning a civic challenge into a competitive advantage.

• People: Building a culture of continuous learning as infrastructure technology cycles shorten, ensuring the workforce keeps pace with every new investment cycle.

 

The Buffet vs A La Carte Framework for Cloud Strategy

On the question of where workloads should live, Anil offers a practical mental model. Public cloud is the buffet: accessible, cost-efficient, and appropriate for utility functions like email, payroll, and standard business applications. Private infrastructure is a la carte: justified when the organisation's differentiated IP, proprietary processes, or regulatory obligations require it. The world does not move from private to public. It always starts in public and builds private as the business matures and the value of protecting its differentiators increases.

Hybrid infrastructure accelerates this decision-making because AI makes private deployment easier and faster than it has ever been. A data scientist can connect to a public cloud ML environment in 15 minutes or build a private equivalent with the right team. The right answer depends entirely on the sensitivity and strategic value of the data involved.
 

Leadership Through Technology Cycles

On leadership, Anil identifies two principles that have remained constant across every technology shift he has navigated: curiosity and agility. The world is hybrid, he notes, and leaders who anchor to a single model or a fixed point of view get left behind. For those moving from technical roles into business leadership, his advice is direct: translate your technical inputs into business outcomes. Investors think in terms of returns, brand, and project-level impact, not infrastructure specifications. The leaders who cross that bridge earliest are the ones who earn a seat in strategic conversations.

Key Takeaways
 

• India's renewable energy position and grey water availability make it structurally competitive for AI infrastructure investment at a scale that developed markets cannot easily replicate

• Sustainability is a balance sheet lever, not a compliance obligation: every percentage point of PUE improvement is directly measurable as profit

• Data sovereignty is accelerating the maturity of localised cloud infrastructure, a shift that was inevitable as AI workloads became more data-intensive and regulatorily sensitive

• The hybrid cloud model is not a transitional state but a permanent architecture: the ratio of public to private will shift over an organisation's lifecycle, not converge on one answer

 

About Anil Nama

Anil Nama is the Chief Information Officer at CtrlS Datacenters Ltd, where he leads strategy, product innovation, and customer-centric infrastructure services. His career spans over three decades, beginning in the Indian Armed Forces with work on information warfare and network-centric systems, before moving through Airtel's data centre and managed services business. At CtrlS, he was part of the leadership team during the growth and global expansion of Cloud4C, a wholly owned subsidiary that was later acquired by Capgemini. He has also been central to the company's growth across BFSI, SAP workloads, and enterprise infrastructure, as well as its investments in sustainability, immersion cooling, and AI-ready data centre design.